// File generated from our OpenAPI spec by Stainless.

package com.openai.models.completions

import com.fasterxml.jackson.annotation.JsonAnyGetter
import com.fasterxml.jackson.annotation.JsonAnySetter
import com.fasterxml.jackson.annotation.JsonCreator
import com.fasterxml.jackson.annotation.JsonProperty
import com.fasterxml.jackson.core.JsonGenerator
import com.fasterxml.jackson.core.ObjectCodec
import com.fasterxml.jackson.databind.JsonNode
import com.fasterxml.jackson.databind.SerializerProvider
import com.fasterxml.jackson.databind.annotation.JsonDeserialize
import com.fasterxml.jackson.databind.annotation.JsonSerialize
import com.fasterxml.jackson.module.kotlin.jacksonTypeRef
import com.openai.core.BaseDeserializer
import com.openai.core.BaseSerializer
import com.openai.core.Enum
import com.openai.core.ExcludeMissing
import com.openai.core.JsonField
import com.openai.core.JsonMissing
import com.openai.core.JsonValue
import com.openai.core.Params
import com.openai.core.allMaxBy
import com.openai.core.checkRequired
import com.openai.core.getOrThrow
import com.openai.core.http.Headers
import com.openai.core.http.QueryParams
import com.openai.core.toImmutable
import com.openai.errors.OpenAIInvalidDataException
import com.openai.models.chat.completions.ChatCompletionStreamOptions
import java.util.Collections
import java.util.Objects
import java.util.Optional
import kotlin.jvm.optionals.getOrNull

/** Creates a completion for the provided prompt and parameters. */
class CompletionCreateParams
private constructor(
    private val body: Body,
    private val additionalHeaders: Headers,
    private val additionalQueryParams: QueryParams,
) : Params {

    /**
     * ID of the model to use. You can use the
     * [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of
     * your available models, or see our [Model overview](https://platform.openai.com/docs/models)
     * for descriptions of them.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type or is
     *   unexpectedly missing or null (e.g. if the server responded with an unexpected value).
     */
    fun model(): Model = body.model()

    /**
     * The prompt(s) to generate completions for, encoded as a string, array of strings, array of
     * tokens, or array of token arrays.
     *
     * Note that <|endoftext|> is the document separator that the model sees during training, so if
     * a prompt is not specified the model will generate as if from the beginning of a new document.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun prompt(): Optional<Prompt> = body.prompt()

    /**
     * Generates `best_of` completions server-side and returns the "best" (the one with the highest
     * log probability per token). Results cannot be streamed.
     *
     * When used with `n`, `best_of` controls the number of candidate completions and `n` specifies
     * how many to return – `best_of` must be greater than `n`.
     *
     * **Note:** Because this parameter generates many completions, it can quickly consume your
     * token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and
     * `stop`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun bestOf(): Optional<Long> = body.bestOf()

    /**
     * Echo back the prompt in addition to the completion
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun echo(): Optional<Boolean> = body.echo()

    /**
     * Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing
     * frequency in the text so far, decreasing the model's likelihood to repeat the same line
     * verbatim.
     *
     * [See more information about frequency and presence
     * penalties.](https://platform.openai.com/docs/guides/text-generation)
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun frequencyPenalty(): Optional<Double> = body.frequencyPenalty()

    /**
     * Modify the likelihood of specified tokens appearing in the completion.
     *
     * Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to
     * an associated bias value from -100 to 100. You can use this
     * [tokenizer tool](/tokenizer?view=bpe) to convert text to token IDs. Mathematically, the bias
     * is added to the logits generated by the model prior to sampling. The exact effect will vary
     * per model, but values between -1 and 1 should decrease or increase likelihood of selection;
     * values like -100 or 100 should result in a ban or exclusive selection of the relevant token.
     *
     * As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from being
     * generated.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun logitBias(): Optional<LogitBias> = body.logitBias()

    /**
     * Include the log probabilities on the `logprobs` most likely output tokens, as well the chosen
     * tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely
     * tokens. The API will always return the `logprob` of the sampled token, so there may be up to
     * `logprobs+1` elements in the response.
     *
     * The maximum value for `logprobs` is 5.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun logprobs(): Optional<Long> = body.logprobs()

    /**
     * The maximum number of [tokens](/tokenizer) that can be generated in the completion.
     *
     * The token count of your prompt plus `max_tokens` cannot exceed the model's context length.
     * [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken)
     * for counting tokens.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun maxTokens(): Optional<Long> = body.maxTokens()

    /**
     * How many completions to generate for each prompt.
     *
     * **Note:** Because this parameter generates many completions, it can quickly consume your
     * token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and
     * `stop`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun n(): Optional<Long> = body.n()

    /**
     * Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear
     * in the text so far, increasing the model's likelihood to talk about new topics.
     *
     * [See more information about frequency and presence
     * penalties.](https://platform.openai.com/docs/guides/text-generation)
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun presencePenalty(): Optional<Double> = body.presencePenalty()

    /**
     * If specified, our system will make a best effort to sample deterministically, such that
     * repeated requests with the same `seed` and parameters should return the same result.
     *
     * Determinism is not guaranteed, and you should refer to the `system_fingerprint` response
     * parameter to monitor changes in the backend.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun seed(): Optional<Long> = body.seed()

    /**
     * Not supported with latest reasoning models `o3` and `o4-mini`.
     *
     * Up to 4 sequences where the API will stop generating further tokens. The returned text will
     * not contain the stop sequence.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun stop(): Optional<Stop> = body.stop()

    /**
     * Options for streaming response. Only set this when you set `stream: true`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun streamOptions(): Optional<ChatCompletionStreamOptions> = body.streamOptions()

    /**
     * The suffix that comes after a completion of inserted text.
     *
     * This parameter is only supported for `gpt-3.5-turbo-instruct`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun suffix(): Optional<String> = body.suffix()

    /**
     * What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the
     * output more random, while lower values like 0.2 will make it more focused and deterministic.
     *
     * We generally recommend altering this or `top_p` but not both.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun temperature(): Optional<Double> = body.temperature()

    /**
     * An alternative to sampling with temperature, called nucleus sampling, where the model
     * considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens
     * comprising the top 10% probability mass are considered.
     *
     * We generally recommend altering this or `temperature` but not both.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun topP(): Optional<Double> = body.topP()

    /**
     * A unique identifier representing your end-user, which can help OpenAI to monitor and detect
     * abuse.
     * [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun user(): Optional<String> = body.user()

    /**
     * Returns the raw JSON value of [model].
     *
     * Unlike [model], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _model(): JsonField<Model> = body._model()

    /**
     * Returns the raw JSON value of [prompt].
     *
     * Unlike [prompt], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _prompt(): JsonField<Prompt> = body._prompt()

    /**
     * Returns the raw JSON value of [bestOf].
     *
     * Unlike [bestOf], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _bestOf(): JsonField<Long> = body._bestOf()

    /**
     * Returns the raw JSON value of [echo].
     *
     * Unlike [echo], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _echo(): JsonField<Boolean> = body._echo()

    /**
     * Returns the raw JSON value of [frequencyPenalty].
     *
     * Unlike [frequencyPenalty], this method doesn't throw if the JSON field has an unexpected
     * type.
     */
    fun _frequencyPenalty(): JsonField<Double> = body._frequencyPenalty()

    /**
     * Returns the raw JSON value of [logitBias].
     *
     * Unlike [logitBias], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _logitBias(): JsonField<LogitBias> = body._logitBias()

    /**
     * Returns the raw JSON value of [logprobs].
     *
     * Unlike [logprobs], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _logprobs(): JsonField<Long> = body._logprobs()

    /**
     * Returns the raw JSON value of [maxTokens].
     *
     * Unlike [maxTokens], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _maxTokens(): JsonField<Long> = body._maxTokens()

    /**
     * Returns the raw JSON value of [n].
     *
     * Unlike [n], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _n(): JsonField<Long> = body._n()

    /**
     * Returns the raw JSON value of [presencePenalty].
     *
     * Unlike [presencePenalty], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _presencePenalty(): JsonField<Double> = body._presencePenalty()

    /**
     * Returns the raw JSON value of [seed].
     *
     * Unlike [seed], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _seed(): JsonField<Long> = body._seed()

    /**
     * Returns the raw JSON value of [stop].
     *
     * Unlike [stop], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _stop(): JsonField<Stop> = body._stop()

    /**
     * Returns the raw JSON value of [streamOptions].
     *
     * Unlike [streamOptions], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _streamOptions(): JsonField<ChatCompletionStreamOptions> = body._streamOptions()

    /**
     * Returns the raw JSON value of [suffix].
     *
     * Unlike [suffix], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _suffix(): JsonField<String> = body._suffix()

    /**
     * Returns the raw JSON value of [temperature].
     *
     * Unlike [temperature], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _temperature(): JsonField<Double> = body._temperature()

    /**
     * Returns the raw JSON value of [topP].
     *
     * Unlike [topP], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _topP(): JsonField<Double> = body._topP()

    /**
     * Returns the raw JSON value of [user].
     *
     * Unlike [user], this method doesn't throw if the JSON field has an unexpected type.
     */
    fun _user(): JsonField<String> = body._user()

    fun _additionalBodyProperties(): Map<String, JsonValue> = body._additionalProperties()

    fun _additionalHeaders(): Headers = additionalHeaders

    fun _additionalQueryParams(): QueryParams = additionalQueryParams

    fun toBuilder() = Builder().from(this)

    companion object {

        /**
         * Returns a mutable builder for constructing an instance of [CompletionCreateParams].
         *
         * The following fields are required:
         * ```java
         * .model()
         * .prompt()
         * ```
         */
        @JvmStatic fun builder() = Builder()
    }

    /** A builder for [CompletionCreateParams]. */
    class Builder internal constructor() {

        private var body: Body.Builder = Body.builder()
        private var additionalHeaders: Headers.Builder = Headers.builder()
        private var additionalQueryParams: QueryParams.Builder = QueryParams.builder()

        @JvmSynthetic
        internal fun from(completionCreateParams: CompletionCreateParams) = apply {
            body = completionCreateParams.body.toBuilder()
            additionalHeaders = completionCreateParams.additionalHeaders.toBuilder()
            additionalQueryParams = completionCreateParams.additionalQueryParams.toBuilder()
        }

        /**
         * Sets the entire request body.
         *
         * This is generally only useful if you are already constructing the body separately.
         * Otherwise, it's more convenient to use the top-level setters instead:
         * - [model]
         * - [prompt]
         * - [bestOf]
         * - [echo]
         * - [frequencyPenalty]
         * - etc.
         */
        fun body(body: Body) = apply { this.body = body.toBuilder() }

        /**
         * ID of the model to use. You can use the
         * [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all
         * of your available models, or see our
         * [Model overview](https://platform.openai.com/docs/models) for descriptions of them.
         */
        fun model(model: Model) = apply { body.model(model) }

        /**
         * Sets [Builder.model] to an arbitrary JSON value.
         *
         * You should usually call [Builder.model] with a well-typed [Model] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun model(model: JsonField<Model>) = apply { body.model(model) }

        /**
         * Sets [model] to an arbitrary [String].
         *
         * You should usually call [model] with a well-typed [Model] constant instead. This method
         * is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun model(value: String) = apply { body.model(value) }

        /**
         * The prompt(s) to generate completions for, encoded as a string, array of strings, array
         * of tokens, or array of token arrays.
         *
         * Note that <|endoftext|> is the document separator that the model sees during training, so
         * if a prompt is not specified the model will generate as if from the beginning of a new
         * document.
         */
        fun prompt(prompt: Prompt?) = apply { body.prompt(prompt) }

        /** Alias for calling [Builder.prompt] with `prompt.orElse(null)`. */
        fun prompt(prompt: Optional<Prompt>) = prompt(prompt.getOrNull())

        /**
         * Sets [Builder.prompt] to an arbitrary JSON value.
         *
         * You should usually call [Builder.prompt] with a well-typed [Prompt] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun prompt(prompt: JsonField<Prompt>) = apply { body.prompt(prompt) }

        /** Alias for calling [prompt] with `Prompt.ofString(string)`. */
        fun prompt(string: String) = apply { body.prompt(string) }

        /** Alias for calling [prompt] with `Prompt.ofArrayOfStrings(arrayOfStrings)`. */
        fun promptOfArrayOfStrings(arrayOfStrings: List<String>) = apply {
            body.promptOfArrayOfStrings(arrayOfStrings)
        }

        /** Alias for calling [prompt] with `Prompt.ofArrayOfTokens(arrayOfTokens)`. */
        fun promptOfArrayOfTokens(arrayOfTokens: List<Long>) = apply {
            body.promptOfArrayOfTokens(arrayOfTokens)
        }

        /** Alias for calling [prompt] with `Prompt.ofArrayOfTokenArrays(arrayOfTokenArrays)`. */
        fun promptOfArrayOfTokenArrays(arrayOfTokenArrays: List<List<Long>>) = apply {
            body.promptOfArrayOfTokenArrays(arrayOfTokenArrays)
        }

        /**
         * Generates `best_of` completions server-side and returns the "best" (the one with the
         * highest log probability per token). Results cannot be streamed.
         *
         * When used with `n`, `best_of` controls the number of candidate completions and `n`
         * specifies how many to return – `best_of` must be greater than `n`.
         *
         * **Note:** Because this parameter generates many completions, it can quickly consume your
         * token quota. Use carefully and ensure that you have reasonable settings for `max_tokens`
         * and `stop`.
         */
        fun bestOf(bestOf: Long?) = apply { body.bestOf(bestOf) }

        /**
         * Alias for [Builder.bestOf].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun bestOf(bestOf: Long) = bestOf(bestOf as Long?)

        /** Alias for calling [Builder.bestOf] with `bestOf.orElse(null)`. */
        fun bestOf(bestOf: Optional<Long>) = bestOf(bestOf.getOrNull())

        /**
         * Sets [Builder.bestOf] to an arbitrary JSON value.
         *
         * You should usually call [Builder.bestOf] with a well-typed [Long] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun bestOf(bestOf: JsonField<Long>) = apply { body.bestOf(bestOf) }

        /** Echo back the prompt in addition to the completion */
        fun echo(echo: Boolean?) = apply { body.echo(echo) }

        /**
         * Alias for [Builder.echo].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun echo(echo: Boolean) = echo(echo as Boolean?)

        /** Alias for calling [Builder.echo] with `echo.orElse(null)`. */
        fun echo(echo: Optional<Boolean>) = echo(echo.getOrNull())

        /**
         * Sets [Builder.echo] to an arbitrary JSON value.
         *
         * You should usually call [Builder.echo] with a well-typed [Boolean] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun echo(echo: JsonField<Boolean>) = apply { body.echo(echo) }

        /**
         * Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing
         * frequency in the text so far, decreasing the model's likelihood to repeat the same line
         * verbatim.
         *
         * [See more information about frequency and presence
         * penalties.](https://platform.openai.com/docs/guides/text-generation)
         */
        fun frequencyPenalty(frequencyPenalty: Double?) = apply {
            body.frequencyPenalty(frequencyPenalty)
        }

        /**
         * Alias for [Builder.frequencyPenalty].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun frequencyPenalty(frequencyPenalty: Double) =
            frequencyPenalty(frequencyPenalty as Double?)

        /** Alias for calling [Builder.frequencyPenalty] with `frequencyPenalty.orElse(null)`. */
        fun frequencyPenalty(frequencyPenalty: Optional<Double>) =
            frequencyPenalty(frequencyPenalty.getOrNull())

        /**
         * Sets [Builder.frequencyPenalty] to an arbitrary JSON value.
         *
         * You should usually call [Builder.frequencyPenalty] with a well-typed [Double] value
         * instead. This method is primarily for setting the field to an undocumented or not yet
         * supported value.
         */
        fun frequencyPenalty(frequencyPenalty: JsonField<Double>) = apply {
            body.frequencyPenalty(frequencyPenalty)
        }

        /**
         * Modify the likelihood of specified tokens appearing in the completion.
         *
         * Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer)
         * to an associated bias value from -100 to 100. You can use this
         * [tokenizer tool](/tokenizer?view=bpe) to convert text to token IDs. Mathematically, the
         * bias is added to the logits generated by the model prior to sampling. The exact effect
         * will vary per model, but values between -1 and 1 should decrease or increase likelihood
         * of selection; values like -100 or 100 should result in a ban or exclusive selection of
         * the relevant token.
         *
         * As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from
         * being generated.
         */
        fun logitBias(logitBias: LogitBias?) = apply { body.logitBias(logitBias) }

        /** Alias for calling [Builder.logitBias] with `logitBias.orElse(null)`. */
        fun logitBias(logitBias: Optional<LogitBias>) = logitBias(logitBias.getOrNull())

        /**
         * Sets [Builder.logitBias] to an arbitrary JSON value.
         *
         * You should usually call [Builder.logitBias] with a well-typed [LogitBias] value instead.
         * This method is primarily for setting the field to an undocumented or not yet supported
         * value.
         */
        fun logitBias(logitBias: JsonField<LogitBias>) = apply { body.logitBias(logitBias) }

        /**
         * Include the log probabilities on the `logprobs` most likely output tokens, as well the
         * chosen tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most
         * likely tokens. The API will always return the `logprob` of the sampled token, so there
         * may be up to `logprobs+1` elements in the response.
         *
         * The maximum value for `logprobs` is 5.
         */
        fun logprobs(logprobs: Long?) = apply { body.logprobs(logprobs) }

        /**
         * Alias for [Builder.logprobs].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun logprobs(logprobs: Long) = logprobs(logprobs as Long?)

        /** Alias for calling [Builder.logprobs] with `logprobs.orElse(null)`. */
        fun logprobs(logprobs: Optional<Long>) = logprobs(logprobs.getOrNull())

        /**
         * Sets [Builder.logprobs] to an arbitrary JSON value.
         *
         * You should usually call [Builder.logprobs] with a well-typed [Long] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun logprobs(logprobs: JsonField<Long>) = apply { body.logprobs(logprobs) }

        /**
         * The maximum number of [tokens](/tokenizer) that can be generated in the completion.
         *
         * The token count of your prompt plus `max_tokens` cannot exceed the model's context
         * length.
         * [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken)
         * for counting tokens.
         */
        fun maxTokens(maxTokens: Long?) = apply { body.maxTokens(maxTokens) }

        /**
         * Alias for [Builder.maxTokens].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun maxTokens(maxTokens: Long) = maxTokens(maxTokens as Long?)

        /** Alias for calling [Builder.maxTokens] with `maxTokens.orElse(null)`. */
        fun maxTokens(maxTokens: Optional<Long>) = maxTokens(maxTokens.getOrNull())

        /**
         * Sets [Builder.maxTokens] to an arbitrary JSON value.
         *
         * You should usually call [Builder.maxTokens] with a well-typed [Long] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun maxTokens(maxTokens: JsonField<Long>) = apply { body.maxTokens(maxTokens) }

        /**
         * How many completions to generate for each prompt.
         *
         * **Note:** Because this parameter generates many completions, it can quickly consume your
         * token quota. Use carefully and ensure that you have reasonable settings for `max_tokens`
         * and `stop`.
         */
        fun n(n: Long?) = apply { body.n(n) }

        /**
         * Alias for [Builder.n].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun n(n: Long) = n(n as Long?)

        /** Alias for calling [Builder.n] with `n.orElse(null)`. */
        fun n(n: Optional<Long>) = n(n.getOrNull())

        /**
         * Sets [Builder.n] to an arbitrary JSON value.
         *
         * You should usually call [Builder.n] with a well-typed [Long] value instead. This method
         * is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun n(n: JsonField<Long>) = apply { body.n(n) }

        /**
         * Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they
         * appear in the text so far, increasing the model's likelihood to talk about new topics.
         *
         * [See more information about frequency and presence
         * penalties.](https://platform.openai.com/docs/guides/text-generation)
         */
        fun presencePenalty(presencePenalty: Double?) = apply {
            body.presencePenalty(presencePenalty)
        }

        /**
         * Alias for [Builder.presencePenalty].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun presencePenalty(presencePenalty: Double) = presencePenalty(presencePenalty as Double?)

        /** Alias for calling [Builder.presencePenalty] with `presencePenalty.orElse(null)`. */
        fun presencePenalty(presencePenalty: Optional<Double>) =
            presencePenalty(presencePenalty.getOrNull())

        /**
         * Sets [Builder.presencePenalty] to an arbitrary JSON value.
         *
         * You should usually call [Builder.presencePenalty] with a well-typed [Double] value
         * instead. This method is primarily for setting the field to an undocumented or not yet
         * supported value.
         */
        fun presencePenalty(presencePenalty: JsonField<Double>) = apply {
            body.presencePenalty(presencePenalty)
        }

        /**
         * If specified, our system will make a best effort to sample deterministically, such that
         * repeated requests with the same `seed` and parameters should return the same result.
         *
         * Determinism is not guaranteed, and you should refer to the `system_fingerprint` response
         * parameter to monitor changes in the backend.
         */
        fun seed(seed: Long?) = apply { body.seed(seed) }

        /**
         * Alias for [Builder.seed].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun seed(seed: Long) = seed(seed as Long?)

        /** Alias for calling [Builder.seed] with `seed.orElse(null)`. */
        fun seed(seed: Optional<Long>) = seed(seed.getOrNull())

        /**
         * Sets [Builder.seed] to an arbitrary JSON value.
         *
         * You should usually call [Builder.seed] with a well-typed [Long] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun seed(seed: JsonField<Long>) = apply { body.seed(seed) }

        /**
         * Not supported with latest reasoning models `o3` and `o4-mini`.
         *
         * Up to 4 sequences where the API will stop generating further tokens. The returned text
         * will not contain the stop sequence.
         */
        fun stop(stop: Stop?) = apply { body.stop(stop) }

        /** Alias for calling [Builder.stop] with `stop.orElse(null)`. */
        fun stop(stop: Optional<Stop>) = stop(stop.getOrNull())

        /**
         * Sets [Builder.stop] to an arbitrary JSON value.
         *
         * You should usually call [Builder.stop] with a well-typed [Stop] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun stop(stop: JsonField<Stop>) = apply { body.stop(stop) }

        /** Alias for calling [stop] with `Stop.ofString(string)`. */
        fun stop(string: String) = apply { body.stop(string) }

        /** Alias for calling [stop] with `Stop.ofStrings(strings)`. */
        fun stopOfStrings(strings: List<String>) = apply { body.stopOfStrings(strings) }

        /** Options for streaming response. Only set this when you set `stream: true`. */
        fun streamOptions(streamOptions: ChatCompletionStreamOptions?) = apply {
            body.streamOptions(streamOptions)
        }

        /** Alias for calling [Builder.streamOptions] with `streamOptions.orElse(null)`. */
        fun streamOptions(streamOptions: Optional<ChatCompletionStreamOptions>) =
            streamOptions(streamOptions.getOrNull())

        /**
         * Sets [Builder.streamOptions] to an arbitrary JSON value.
         *
         * You should usually call [Builder.streamOptions] with a well-typed
         * [ChatCompletionStreamOptions] value instead. This method is primarily for setting the
         * field to an undocumented or not yet supported value.
         */
        fun streamOptions(streamOptions: JsonField<ChatCompletionStreamOptions>) = apply {
            body.streamOptions(streamOptions)
        }

        /**
         * The suffix that comes after a completion of inserted text.
         *
         * This parameter is only supported for `gpt-3.5-turbo-instruct`.
         */
        fun suffix(suffix: String?) = apply { body.suffix(suffix) }

        /** Alias for calling [Builder.suffix] with `suffix.orElse(null)`. */
        fun suffix(suffix: Optional<String>) = suffix(suffix.getOrNull())

        /**
         * Sets [Builder.suffix] to an arbitrary JSON value.
         *
         * You should usually call [Builder.suffix] with a well-typed [String] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun suffix(suffix: JsonField<String>) = apply { body.suffix(suffix) }

        /**
         * What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the
         * output more random, while lower values like 0.2 will make it more focused and
         * deterministic.
         *
         * We generally recommend altering this or `top_p` but not both.
         */
        fun temperature(temperature: Double?) = apply { body.temperature(temperature) }

        /**
         * Alias for [Builder.temperature].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun temperature(temperature: Double) = temperature(temperature as Double?)

        /** Alias for calling [Builder.temperature] with `temperature.orElse(null)`. */
        fun temperature(temperature: Optional<Double>) = temperature(temperature.getOrNull())

        /**
         * Sets [Builder.temperature] to an arbitrary JSON value.
         *
         * You should usually call [Builder.temperature] with a well-typed [Double] value instead.
         * This method is primarily for setting the field to an undocumented or not yet supported
         * value.
         */
        fun temperature(temperature: JsonField<Double>) = apply { body.temperature(temperature) }

        /**
         * An alternative to sampling with temperature, called nucleus sampling, where the model
         * considers the results of the tokens with top_p probability mass. So 0.1 means only the
         * tokens comprising the top 10% probability mass are considered.
         *
         * We generally recommend altering this or `temperature` but not both.
         */
        fun topP(topP: Double?) = apply { body.topP(topP) }

        /**
         * Alias for [Builder.topP].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun topP(topP: Double) = topP(topP as Double?)

        /** Alias for calling [Builder.topP] with `topP.orElse(null)`. */
        fun topP(topP: Optional<Double>) = topP(topP.getOrNull())

        /**
         * Sets [Builder.topP] to an arbitrary JSON value.
         *
         * You should usually call [Builder.topP] with a well-typed [Double] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun topP(topP: JsonField<Double>) = apply { body.topP(topP) }

        /**
         * A unique identifier representing your end-user, which can help OpenAI to monitor and
         * detect abuse.
         * [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
         */
        fun user(user: String) = apply { body.user(user) }

        /**
         * Sets [Builder.user] to an arbitrary JSON value.
         *
         * You should usually call [Builder.user] with a well-typed [String] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun user(user: JsonField<String>) = apply { body.user(user) }

        fun additionalBodyProperties(additionalBodyProperties: Map<String, JsonValue>) = apply {
            body.additionalProperties(additionalBodyProperties)
        }

        fun putAdditionalBodyProperty(key: String, value: JsonValue) = apply {
            body.putAdditionalProperty(key, value)
        }

        fun putAllAdditionalBodyProperties(additionalBodyProperties: Map<String, JsonValue>) =
            apply {
                body.putAllAdditionalProperties(additionalBodyProperties)
            }

        fun removeAdditionalBodyProperty(key: String) = apply { body.removeAdditionalProperty(key) }

        fun removeAllAdditionalBodyProperties(keys: Set<String>) = apply {
            body.removeAllAdditionalProperties(keys)
        }

        fun additionalHeaders(additionalHeaders: Headers) = apply {
            this.additionalHeaders.clear()
            putAllAdditionalHeaders(additionalHeaders)
        }

        fun additionalHeaders(additionalHeaders: Map<String, Iterable<String>>) = apply {
            this.additionalHeaders.clear()
            putAllAdditionalHeaders(additionalHeaders)
        }

        fun putAdditionalHeader(name: String, value: String) = apply {
            additionalHeaders.put(name, value)
        }

        fun putAdditionalHeaders(name: String, values: Iterable<String>) = apply {
            additionalHeaders.put(name, values)
        }

        fun putAllAdditionalHeaders(additionalHeaders: Headers) = apply {
            this.additionalHeaders.putAll(additionalHeaders)
        }

        fun putAllAdditionalHeaders(additionalHeaders: Map<String, Iterable<String>>) = apply {
            this.additionalHeaders.putAll(additionalHeaders)
        }

        fun replaceAdditionalHeaders(name: String, value: String) = apply {
            additionalHeaders.replace(name, value)
        }

        fun replaceAdditionalHeaders(name: String, values: Iterable<String>) = apply {
            additionalHeaders.replace(name, values)
        }

        fun replaceAllAdditionalHeaders(additionalHeaders: Headers) = apply {
            this.additionalHeaders.replaceAll(additionalHeaders)
        }

        fun replaceAllAdditionalHeaders(additionalHeaders: Map<String, Iterable<String>>) = apply {
            this.additionalHeaders.replaceAll(additionalHeaders)
        }

        fun removeAdditionalHeaders(name: String) = apply { additionalHeaders.remove(name) }

        fun removeAllAdditionalHeaders(names: Set<String>) = apply {
            additionalHeaders.removeAll(names)
        }

        fun additionalQueryParams(additionalQueryParams: QueryParams) = apply {
            this.additionalQueryParams.clear()
            putAllAdditionalQueryParams(additionalQueryParams)
        }

        fun additionalQueryParams(additionalQueryParams: Map<String, Iterable<String>>) = apply {
            this.additionalQueryParams.clear()
            putAllAdditionalQueryParams(additionalQueryParams)
        }

        fun putAdditionalQueryParam(key: String, value: String) = apply {
            additionalQueryParams.put(key, value)
        }

        fun putAdditionalQueryParams(key: String, values: Iterable<String>) = apply {
            additionalQueryParams.put(key, values)
        }

        fun putAllAdditionalQueryParams(additionalQueryParams: QueryParams) = apply {
            this.additionalQueryParams.putAll(additionalQueryParams)
        }

        fun putAllAdditionalQueryParams(additionalQueryParams: Map<String, Iterable<String>>) =
            apply {
                this.additionalQueryParams.putAll(additionalQueryParams)
            }

        fun replaceAdditionalQueryParams(key: String, value: String) = apply {
            additionalQueryParams.replace(key, value)
        }

        fun replaceAdditionalQueryParams(key: String, values: Iterable<String>) = apply {
            additionalQueryParams.replace(key, values)
        }

        fun replaceAllAdditionalQueryParams(additionalQueryParams: QueryParams) = apply {
            this.additionalQueryParams.replaceAll(additionalQueryParams)
        }

        fun replaceAllAdditionalQueryParams(additionalQueryParams: Map<String, Iterable<String>>) =
            apply {
                this.additionalQueryParams.replaceAll(additionalQueryParams)
            }

        fun removeAdditionalQueryParams(key: String) = apply { additionalQueryParams.remove(key) }

        fun removeAllAdditionalQueryParams(keys: Set<String>) = apply {
            additionalQueryParams.removeAll(keys)
        }

        /**
         * Returns an immutable instance of [CompletionCreateParams].
         *
         * Further updates to this [Builder] will not mutate the returned instance.
         *
         * The following fields are required:
         * ```java
         * .model()
         * .prompt()
         * ```
         *
         * @throws IllegalStateException if any required field is unset.
         */
        fun build(): CompletionCreateParams =
            CompletionCreateParams(
                body.build(),
                additionalHeaders.build(),
                additionalQueryParams.build(),
            )
    }

    fun _body(): Body = body

    override fun _headers(): Headers = additionalHeaders

    override fun _queryParams(): QueryParams = additionalQueryParams

    class Body
    private constructor(
        private val model: JsonField<Model>,
        private val prompt: JsonField<Prompt>,
        private val bestOf: JsonField<Long>,
        private val echo: JsonField<Boolean>,
        private val frequencyPenalty: JsonField<Double>,
        private val logitBias: JsonField<LogitBias>,
        private val logprobs: JsonField<Long>,
        private val maxTokens: JsonField<Long>,
        private val n: JsonField<Long>,
        private val presencePenalty: JsonField<Double>,
        private val seed: JsonField<Long>,
        private val stop: JsonField<Stop>,
        private val streamOptions: JsonField<ChatCompletionStreamOptions>,
        private val suffix: JsonField<String>,
        private val temperature: JsonField<Double>,
        private val topP: JsonField<Double>,
        private val user: JsonField<String>,
        private val additionalProperties: MutableMap<String, JsonValue>,
    ) {

        @JsonCreator
        private constructor(
            @JsonProperty("model") @ExcludeMissing model: JsonField<Model> = JsonMissing.of(),
            @JsonProperty("prompt") @ExcludeMissing prompt: JsonField<Prompt> = JsonMissing.of(),
            @JsonProperty("best_of") @ExcludeMissing bestOf: JsonField<Long> = JsonMissing.of(),
            @JsonProperty("echo") @ExcludeMissing echo: JsonField<Boolean> = JsonMissing.of(),
            @JsonProperty("frequency_penalty")
            @ExcludeMissing
            frequencyPenalty: JsonField<Double> = JsonMissing.of(),
            @JsonProperty("logit_bias")
            @ExcludeMissing
            logitBias: JsonField<LogitBias> = JsonMissing.of(),
            @JsonProperty("logprobs") @ExcludeMissing logprobs: JsonField<Long> = JsonMissing.of(),
            @JsonProperty("max_tokens")
            @ExcludeMissing
            maxTokens: JsonField<Long> = JsonMissing.of(),
            @JsonProperty("n") @ExcludeMissing n: JsonField<Long> = JsonMissing.of(),
            @JsonProperty("presence_penalty")
            @ExcludeMissing
            presencePenalty: JsonField<Double> = JsonMissing.of(),
            @JsonProperty("seed") @ExcludeMissing seed: JsonField<Long> = JsonMissing.of(),
            @JsonProperty("stop") @ExcludeMissing stop: JsonField<Stop> = JsonMissing.of(),
            @JsonProperty("stream_options")
            @ExcludeMissing
            streamOptions: JsonField<ChatCompletionStreamOptions> = JsonMissing.of(),
            @JsonProperty("suffix") @ExcludeMissing suffix: JsonField<String> = JsonMissing.of(),
            @JsonProperty("temperature")
            @ExcludeMissing
            temperature: JsonField<Double> = JsonMissing.of(),
            @JsonProperty("top_p") @ExcludeMissing topP: JsonField<Double> = JsonMissing.of(),
            @JsonProperty("user") @ExcludeMissing user: JsonField<String> = JsonMissing.of(),
        ) : this(
            model,
            prompt,
            bestOf,
            echo,
            frequencyPenalty,
            logitBias,
            logprobs,
            maxTokens,
            n,
            presencePenalty,
            seed,
            stop,
            streamOptions,
            suffix,
            temperature,
            topP,
            user,
            mutableMapOf(),
        )

        /**
         * ID of the model to use. You can use the
         * [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all
         * of your available models, or see our
         * [Model overview](https://platform.openai.com/docs/models) for descriptions of them.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type or is
         *   unexpectedly missing or null (e.g. if the server responded with an unexpected value).
         */
        fun model(): Model = model.getRequired("model")

        /**
         * The prompt(s) to generate completions for, encoded as a string, array of strings, array
         * of tokens, or array of token arrays.
         *
         * Note that <|endoftext|> is the document separator that the model sees during training, so
         * if a prompt is not specified the model will generate as if from the beginning of a new
         * document.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun prompt(): Optional<Prompt> = prompt.getOptional("prompt")

        /**
         * Generates `best_of` completions server-side and returns the "best" (the one with the
         * highest log probability per token). Results cannot be streamed.
         *
         * When used with `n`, `best_of` controls the number of candidate completions and `n`
         * specifies how many to return – `best_of` must be greater than `n`.
         *
         * **Note:** Because this parameter generates many completions, it can quickly consume your
         * token quota. Use carefully and ensure that you have reasonable settings for `max_tokens`
         * and `stop`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun bestOf(): Optional<Long> = bestOf.getOptional("best_of")

        /**
         * Echo back the prompt in addition to the completion
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun echo(): Optional<Boolean> = echo.getOptional("echo")

        /**
         * Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing
         * frequency in the text so far, decreasing the model's likelihood to repeat the same line
         * verbatim.
         *
         * [See more information about frequency and presence
         * penalties.](https://platform.openai.com/docs/guides/text-generation)
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun frequencyPenalty(): Optional<Double> = frequencyPenalty.getOptional("frequency_penalty")

        /**
         * Modify the likelihood of specified tokens appearing in the completion.
         *
         * Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer)
         * to an associated bias value from -100 to 100. You can use this
         * [tokenizer tool](/tokenizer?view=bpe) to convert text to token IDs. Mathematically, the
         * bias is added to the logits generated by the model prior to sampling. The exact effect
         * will vary per model, but values between -1 and 1 should decrease or increase likelihood
         * of selection; values like -100 or 100 should result in a ban or exclusive selection of
         * the relevant token.
         *
         * As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from
         * being generated.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun logitBias(): Optional<LogitBias> = logitBias.getOptional("logit_bias")

        /**
         * Include the log probabilities on the `logprobs` most likely output tokens, as well the
         * chosen tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most
         * likely tokens. The API will always return the `logprob` of the sampled token, so there
         * may be up to `logprobs+1` elements in the response.
         *
         * The maximum value for `logprobs` is 5.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun logprobs(): Optional<Long> = logprobs.getOptional("logprobs")

        /**
         * The maximum number of [tokens](/tokenizer) that can be generated in the completion.
         *
         * The token count of your prompt plus `max_tokens` cannot exceed the model's context
         * length.
         * [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken)
         * for counting tokens.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun maxTokens(): Optional<Long> = maxTokens.getOptional("max_tokens")

        /**
         * How many completions to generate for each prompt.
         *
         * **Note:** Because this parameter generates many completions, it can quickly consume your
         * token quota. Use carefully and ensure that you have reasonable settings for `max_tokens`
         * and `stop`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun n(): Optional<Long> = n.getOptional("n")

        /**
         * Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they
         * appear in the text so far, increasing the model's likelihood to talk about new topics.
         *
         * [See more information about frequency and presence
         * penalties.](https://platform.openai.com/docs/guides/text-generation)
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun presencePenalty(): Optional<Double> = presencePenalty.getOptional("presence_penalty")

        /**
         * If specified, our system will make a best effort to sample deterministically, such that
         * repeated requests with the same `seed` and parameters should return the same result.
         *
         * Determinism is not guaranteed, and you should refer to the `system_fingerprint` response
         * parameter to monitor changes in the backend.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun seed(): Optional<Long> = seed.getOptional("seed")

        /**
         * Not supported with latest reasoning models `o3` and `o4-mini`.
         *
         * Up to 4 sequences where the API will stop generating further tokens. The returned text
         * will not contain the stop sequence.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun stop(): Optional<Stop> = stop.getOptional("stop")

        /**
         * Options for streaming response. Only set this when you set `stream: true`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun streamOptions(): Optional<ChatCompletionStreamOptions> =
            streamOptions.getOptional("stream_options")

        /**
         * The suffix that comes after a completion of inserted text.
         *
         * This parameter is only supported for `gpt-3.5-turbo-instruct`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun suffix(): Optional<String> = suffix.getOptional("suffix")

        /**
         * What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the
         * output more random, while lower values like 0.2 will make it more focused and
         * deterministic.
         *
         * We generally recommend altering this or `top_p` but not both.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun temperature(): Optional<Double> = temperature.getOptional("temperature")

        /**
         * An alternative to sampling with temperature, called nucleus sampling, where the model
         * considers the results of the tokens with top_p probability mass. So 0.1 means only the
         * tokens comprising the top 10% probability mass are considered.
         *
         * We generally recommend altering this or `temperature` but not both.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun topP(): Optional<Double> = topP.getOptional("top_p")

        /**
         * A unique identifier representing your end-user, which can help OpenAI to monitor and
         * detect abuse.
         * [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun user(): Optional<String> = user.getOptional("user")

        /**
         * Returns the raw JSON value of [model].
         *
         * Unlike [model], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("model") @ExcludeMissing fun _model(): JsonField<Model> = model

        /**
         * Returns the raw JSON value of [prompt].
         *
         * Unlike [prompt], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("prompt") @ExcludeMissing fun _prompt(): JsonField<Prompt> = prompt

        /**
         * Returns the raw JSON value of [bestOf].
         *
         * Unlike [bestOf], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("best_of") @ExcludeMissing fun _bestOf(): JsonField<Long> = bestOf

        /**
         * Returns the raw JSON value of [echo].
         *
         * Unlike [echo], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("echo") @ExcludeMissing fun _echo(): JsonField<Boolean> = echo

        /**
         * Returns the raw JSON value of [frequencyPenalty].
         *
         * Unlike [frequencyPenalty], this method doesn't throw if the JSON field has an unexpected
         * type.
         */
        @JsonProperty("frequency_penalty")
        @ExcludeMissing
        fun _frequencyPenalty(): JsonField<Double> = frequencyPenalty

        /**
         * Returns the raw JSON value of [logitBias].
         *
         * Unlike [logitBias], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("logit_bias")
        @ExcludeMissing
        fun _logitBias(): JsonField<LogitBias> = logitBias

        /**
         * Returns the raw JSON value of [logprobs].
         *
         * Unlike [logprobs], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("logprobs") @ExcludeMissing fun _logprobs(): JsonField<Long> = logprobs

        /**
         * Returns the raw JSON value of [maxTokens].
         *
         * Unlike [maxTokens], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("max_tokens") @ExcludeMissing fun _maxTokens(): JsonField<Long> = maxTokens

        /**
         * Returns the raw JSON value of [n].
         *
         * Unlike [n], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("n") @ExcludeMissing fun _n(): JsonField<Long> = n

        /**
         * Returns the raw JSON value of [presencePenalty].
         *
         * Unlike [presencePenalty], this method doesn't throw if the JSON field has an unexpected
         * type.
         */
        @JsonProperty("presence_penalty")
        @ExcludeMissing
        fun _presencePenalty(): JsonField<Double> = presencePenalty

        /**
         * Returns the raw JSON value of [seed].
         *
         * Unlike [seed], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("seed") @ExcludeMissing fun _seed(): JsonField<Long> = seed

        /**
         * Returns the raw JSON value of [stop].
         *
         * Unlike [stop], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("stop") @ExcludeMissing fun _stop(): JsonField<Stop> = stop

        /**
         * Returns the raw JSON value of [streamOptions].
         *
         * Unlike [streamOptions], this method doesn't throw if the JSON field has an unexpected
         * type.
         */
        @JsonProperty("stream_options")
        @ExcludeMissing
        fun _streamOptions(): JsonField<ChatCompletionStreamOptions> = streamOptions

        /**
         * Returns the raw JSON value of [suffix].
         *
         * Unlike [suffix], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("suffix") @ExcludeMissing fun _suffix(): JsonField<String> = suffix

        /**
         * Returns the raw JSON value of [temperature].
         *
         * Unlike [temperature], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("temperature")
        @ExcludeMissing
        fun _temperature(): JsonField<Double> = temperature

        /**
         * Returns the raw JSON value of [topP].
         *
         * Unlike [topP], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("top_p") @ExcludeMissing fun _topP(): JsonField<Double> = topP

        /**
         * Returns the raw JSON value of [user].
         *
         * Unlike [user], this method doesn't throw if the JSON field has an unexpected type.
         */
        @JsonProperty("user") @ExcludeMissing fun _user(): JsonField<String> = user

        @JsonAnySetter
        private fun putAdditionalProperty(key: String, value: JsonValue) {
            additionalProperties.put(key, value)
        }

        @JsonAnyGetter
        @ExcludeMissing
        fun _additionalProperties(): Map<String, JsonValue> =
            Collections.unmodifiableMap(additionalProperties)

        fun toBuilder() = Builder().from(this)

        companion object {

            /**
             * Returns a mutable builder for constructing an instance of [Body].
             *
             * The following fields are required:
             * ```java
             * .model()
             * .prompt()
             * ```
             */
            @JvmStatic fun builder() = Builder()
        }

        /** A builder for [Body]. */
        class Builder internal constructor() {

            private var model: JsonField<Model>? = null
            private var prompt: JsonField<Prompt>? = null
            private var bestOf: JsonField<Long> = JsonMissing.of()
            private var echo: JsonField<Boolean> = JsonMissing.of()
            private var frequencyPenalty: JsonField<Double> = JsonMissing.of()
            private var logitBias: JsonField<LogitBias> = JsonMissing.of()
            private var logprobs: JsonField<Long> = JsonMissing.of()
            private var maxTokens: JsonField<Long> = JsonMissing.of()
            private var n: JsonField<Long> = JsonMissing.of()
            private var presencePenalty: JsonField<Double> = JsonMissing.of()
            private var seed: JsonField<Long> = JsonMissing.of()
            private var stop: JsonField<Stop> = JsonMissing.of()
            private var streamOptions: JsonField<ChatCompletionStreamOptions> = JsonMissing.of()
            private var suffix: JsonField<String> = JsonMissing.of()
            private var temperature: JsonField<Double> = JsonMissing.of()
            private var topP: JsonField<Double> = JsonMissing.of()
            private var user: JsonField<String> = JsonMissing.of()
            private var additionalProperties: MutableMap<String, JsonValue> = mutableMapOf()

            @JvmSynthetic
            internal fun from(body: Body) = apply {
                model = body.model
                prompt = body.prompt
                bestOf = body.bestOf
                echo = body.echo
                frequencyPenalty = body.frequencyPenalty
                logitBias = body.logitBias
                logprobs = body.logprobs
                maxTokens = body.maxTokens
                n = body.n
                presencePenalty = body.presencePenalty
                seed = body.seed
                stop = body.stop
                streamOptions = body.streamOptions
                suffix = body.suffix
                temperature = body.temperature
                topP = body.topP
                user = body.user
                additionalProperties = body.additionalProperties.toMutableMap()
            }

            /**
             * ID of the model to use. You can use the
             * [List models](https://platform.openai.com/docs/api-reference/models/list) API to see
             * all of your available models, or see our
             * [Model overview](https://platform.openai.com/docs/models) for descriptions of them.
             */
            fun model(model: Model) = model(JsonField.of(model))

            /**
             * Sets [Builder.model] to an arbitrary JSON value.
             *
             * You should usually call [Builder.model] with a well-typed [Model] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun model(model: JsonField<Model>) = apply { this.model = model }

            /**
             * Sets [model] to an arbitrary [String].
             *
             * You should usually call [model] with a well-typed [Model] constant instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun model(value: String) = model(Model.of(value))

            /**
             * The prompt(s) to generate completions for, encoded as a string, array of strings,
             * array of tokens, or array of token arrays.
             *
             * Note that <|endoftext|> is the document separator that the model sees during
             * training, so if a prompt is not specified the model will generate as if from the
             * beginning of a new document.
             */
            fun prompt(prompt: Prompt?) = prompt(JsonField.ofNullable(prompt))

            /** Alias for calling [Builder.prompt] with `prompt.orElse(null)`. */
            fun prompt(prompt: Optional<Prompt>) = prompt(prompt.getOrNull())

            /**
             * Sets [Builder.prompt] to an arbitrary JSON value.
             *
             * You should usually call [Builder.prompt] with a well-typed [Prompt] value instead.
             * This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun prompt(prompt: JsonField<Prompt>) = apply { this.prompt = prompt }

            /** Alias for calling [prompt] with `Prompt.ofString(string)`. */
            fun prompt(string: String) = prompt(Prompt.ofString(string))

            /** Alias for calling [prompt] with `Prompt.ofArrayOfStrings(arrayOfStrings)`. */
            fun promptOfArrayOfStrings(arrayOfStrings: List<String>) =
                prompt(Prompt.ofArrayOfStrings(arrayOfStrings))

            /** Alias for calling [prompt] with `Prompt.ofArrayOfTokens(arrayOfTokens)`. */
            fun promptOfArrayOfTokens(arrayOfTokens: List<Long>) =
                prompt(Prompt.ofArrayOfTokens(arrayOfTokens))

            /**
             * Alias for calling [prompt] with `Prompt.ofArrayOfTokenArrays(arrayOfTokenArrays)`.
             */
            fun promptOfArrayOfTokenArrays(arrayOfTokenArrays: List<List<Long>>) =
                prompt(Prompt.ofArrayOfTokenArrays(arrayOfTokenArrays))

            /**
             * Generates `best_of` completions server-side and returns the "best" (the one with the
             * highest log probability per token). Results cannot be streamed.
             *
             * When used with `n`, `best_of` controls the number of candidate completions and `n`
             * specifies how many to return – `best_of` must be greater than `n`.
             *
             * **Note:** Because this parameter generates many completions, it can quickly consume
             * your token quota. Use carefully and ensure that you have reasonable settings for
             * `max_tokens` and `stop`.
             */
            fun bestOf(bestOf: Long?) = bestOf(JsonField.ofNullable(bestOf))

            /**
             * Alias for [Builder.bestOf].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun bestOf(bestOf: Long) = bestOf(bestOf as Long?)

            /** Alias for calling [Builder.bestOf] with `bestOf.orElse(null)`. */
            fun bestOf(bestOf: Optional<Long>) = bestOf(bestOf.getOrNull())

            /**
             * Sets [Builder.bestOf] to an arbitrary JSON value.
             *
             * You should usually call [Builder.bestOf] with a well-typed [Long] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun bestOf(bestOf: JsonField<Long>) = apply { this.bestOf = bestOf }

            /** Echo back the prompt in addition to the completion */
            fun echo(echo: Boolean?) = echo(JsonField.ofNullable(echo))

            /**
             * Alias for [Builder.echo].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun echo(echo: Boolean) = echo(echo as Boolean?)

            /** Alias for calling [Builder.echo] with `echo.orElse(null)`. */
            fun echo(echo: Optional<Boolean>) = echo(echo.getOrNull())

            /**
             * Sets [Builder.echo] to an arbitrary JSON value.
             *
             * You should usually call [Builder.echo] with a well-typed [Boolean] value instead.
             * This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun echo(echo: JsonField<Boolean>) = apply { this.echo = echo }

            /**
             * Number between -2.0 and 2.0. Positive values penalize new tokens based on their
             * existing frequency in the text so far, decreasing the model's likelihood to repeat
             * the same line verbatim.
             *
             * [See more information about frequency and presence
             * penalties.](https://platform.openai.com/docs/guides/text-generation)
             */
            fun frequencyPenalty(frequencyPenalty: Double?) =
                frequencyPenalty(JsonField.ofNullable(frequencyPenalty))

            /**
             * Alias for [Builder.frequencyPenalty].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun frequencyPenalty(frequencyPenalty: Double) =
                frequencyPenalty(frequencyPenalty as Double?)

            /**
             * Alias for calling [Builder.frequencyPenalty] with `frequencyPenalty.orElse(null)`.
             */
            fun frequencyPenalty(frequencyPenalty: Optional<Double>) =
                frequencyPenalty(frequencyPenalty.getOrNull())

            /**
             * Sets [Builder.frequencyPenalty] to an arbitrary JSON value.
             *
             * You should usually call [Builder.frequencyPenalty] with a well-typed [Double] value
             * instead. This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun frequencyPenalty(frequencyPenalty: JsonField<Double>) = apply {
                this.frequencyPenalty = frequencyPenalty
            }

            /**
             * Modify the likelihood of specified tokens appearing in the completion.
             *
             * Accepts a JSON object that maps tokens (specified by their token ID in the GPT
             * tokenizer) to an associated bias value from -100 to 100. You can use this
             * [tokenizer tool](/tokenizer?view=bpe) to convert text to token IDs. Mathematically,
             * the bias is added to the logits generated by the model prior to sampling. The exact
             * effect will vary per model, but values between -1 and 1 should decrease or increase
             * likelihood of selection; values like -100 or 100 should result in a ban or exclusive
             * selection of the relevant token.
             *
             * As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from
             * being generated.
             */
            fun logitBias(logitBias: LogitBias?) = logitBias(JsonField.ofNullable(logitBias))

            /** Alias for calling [Builder.logitBias] with `logitBias.orElse(null)`. */
            fun logitBias(logitBias: Optional<LogitBias>) = logitBias(logitBias.getOrNull())

            /**
             * Sets [Builder.logitBias] to an arbitrary JSON value.
             *
             * You should usually call [Builder.logitBias] with a well-typed [LogitBias] value
             * instead. This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun logitBias(logitBias: JsonField<LogitBias>) = apply { this.logitBias = logitBias }

            /**
             * Include the log probabilities on the `logprobs` most likely output tokens, as well
             * the chosen tokens. For example, if `logprobs` is 5, the API will return a list of the
             * 5 most likely tokens. The API will always return the `logprob` of the sampled token,
             * so there may be up to `logprobs+1` elements in the response.
             *
             * The maximum value for `logprobs` is 5.
             */
            fun logprobs(logprobs: Long?) = logprobs(JsonField.ofNullable(logprobs))

            /**
             * Alias for [Builder.logprobs].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun logprobs(logprobs: Long) = logprobs(logprobs as Long?)

            /** Alias for calling [Builder.logprobs] with `logprobs.orElse(null)`. */
            fun logprobs(logprobs: Optional<Long>) = logprobs(logprobs.getOrNull())

            /**
             * Sets [Builder.logprobs] to an arbitrary JSON value.
             *
             * You should usually call [Builder.logprobs] with a well-typed [Long] value instead.
             * This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun logprobs(logprobs: JsonField<Long>) = apply { this.logprobs = logprobs }

            /**
             * The maximum number of [tokens](/tokenizer) that can be generated in the completion.
             *
             * The token count of your prompt plus `max_tokens` cannot exceed the model's context
             * length.
             * [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken)
             * for counting tokens.
             */
            fun maxTokens(maxTokens: Long?) = maxTokens(JsonField.ofNullable(maxTokens))

            /**
             * Alias for [Builder.maxTokens].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun maxTokens(maxTokens: Long) = maxTokens(maxTokens as Long?)

            /** Alias for calling [Builder.maxTokens] with `maxTokens.orElse(null)`. */
            fun maxTokens(maxTokens: Optional<Long>) = maxTokens(maxTokens.getOrNull())

            /**
             * Sets [Builder.maxTokens] to an arbitrary JSON value.
             *
             * You should usually call [Builder.maxTokens] with a well-typed [Long] value instead.
             * This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun maxTokens(maxTokens: JsonField<Long>) = apply { this.maxTokens = maxTokens }

            /**
             * How many completions to generate for each prompt.
             *
             * **Note:** Because this parameter generates many completions, it can quickly consume
             * your token quota. Use carefully and ensure that you have reasonable settings for
             * `max_tokens` and `stop`.
             */
            fun n(n: Long?) = n(JsonField.ofNullable(n))

            /**
             * Alias for [Builder.n].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun n(n: Long) = n(n as Long?)

            /** Alias for calling [Builder.n] with `n.orElse(null)`. */
            fun n(n: Optional<Long>) = n(n.getOrNull())

            /**
             * Sets [Builder.n] to an arbitrary JSON value.
             *
             * You should usually call [Builder.n] with a well-typed [Long] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun n(n: JsonField<Long>) = apply { this.n = n }

            /**
             * Number between -2.0 and 2.0. Positive values penalize new tokens based on whether
             * they appear in the text so far, increasing the model's likelihood to talk about new
             * topics.
             *
             * [See more information about frequency and presence
             * penalties.](https://platform.openai.com/docs/guides/text-generation)
             */
            fun presencePenalty(presencePenalty: Double?) =
                presencePenalty(JsonField.ofNullable(presencePenalty))

            /**
             * Alias for [Builder.presencePenalty].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun presencePenalty(presencePenalty: Double) =
                presencePenalty(presencePenalty as Double?)

            /** Alias for calling [Builder.presencePenalty] with `presencePenalty.orElse(null)`. */
            fun presencePenalty(presencePenalty: Optional<Double>) =
                presencePenalty(presencePenalty.getOrNull())

            /**
             * Sets [Builder.presencePenalty] to an arbitrary JSON value.
             *
             * You should usually call [Builder.presencePenalty] with a well-typed [Double] value
             * instead. This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun presencePenalty(presencePenalty: JsonField<Double>) = apply {
                this.presencePenalty = presencePenalty
            }

            /**
             * If specified, our system will make a best effort to sample deterministically, such
             * that repeated requests with the same `seed` and parameters should return the same
             * result.
             *
             * Determinism is not guaranteed, and you should refer to the `system_fingerprint`
             * response parameter to monitor changes in the backend.
             */
            fun seed(seed: Long?) = seed(JsonField.ofNullable(seed))

            /**
             * Alias for [Builder.seed].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun seed(seed: Long) = seed(seed as Long?)

            /** Alias for calling [Builder.seed] with `seed.orElse(null)`. */
            fun seed(seed: Optional<Long>) = seed(seed.getOrNull())

            /**
             * Sets [Builder.seed] to an arbitrary JSON value.
             *
             * You should usually call [Builder.seed] with a well-typed [Long] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun seed(seed: JsonField<Long>) = apply { this.seed = seed }

            /**
             * Not supported with latest reasoning models `o3` and `o4-mini`.
             *
             * Up to 4 sequences where the API will stop generating further tokens. The returned
             * text will not contain the stop sequence.
             */
            fun stop(stop: Stop?) = stop(JsonField.ofNullable(stop))

            /** Alias for calling [Builder.stop] with `stop.orElse(null)`. */
            fun stop(stop: Optional<Stop>) = stop(stop.getOrNull())

            /**
             * Sets [Builder.stop] to an arbitrary JSON value.
             *
             * You should usually call [Builder.stop] with a well-typed [Stop] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun stop(stop: JsonField<Stop>) = apply { this.stop = stop }

            /** Alias for calling [stop] with `Stop.ofString(string)`. */
            fun stop(string: String) = stop(Stop.ofString(string))

            /** Alias for calling [stop] with `Stop.ofStrings(strings)`. */
            fun stopOfStrings(strings: List<String>) = stop(Stop.ofStrings(strings))

            /** Options for streaming response. Only set this when you set `stream: true`. */
            fun streamOptions(streamOptions: ChatCompletionStreamOptions?) =
                streamOptions(JsonField.ofNullable(streamOptions))

            /** Alias for calling [Builder.streamOptions] with `streamOptions.orElse(null)`. */
            fun streamOptions(streamOptions: Optional<ChatCompletionStreamOptions>) =
                streamOptions(streamOptions.getOrNull())

            /**
             * Sets [Builder.streamOptions] to an arbitrary JSON value.
             *
             * You should usually call [Builder.streamOptions] with a well-typed
             * [ChatCompletionStreamOptions] value instead. This method is primarily for setting the
             * field to an undocumented or not yet supported value.
             */
            fun streamOptions(streamOptions: JsonField<ChatCompletionStreamOptions>) = apply {
                this.streamOptions = streamOptions
            }

            /**
             * The suffix that comes after a completion of inserted text.
             *
             * This parameter is only supported for `gpt-3.5-turbo-instruct`.
             */
            fun suffix(suffix: String?) = suffix(JsonField.ofNullable(suffix))

            /** Alias for calling [Builder.suffix] with `suffix.orElse(null)`. */
            fun suffix(suffix: Optional<String>) = suffix(suffix.getOrNull())

            /**
             * Sets [Builder.suffix] to an arbitrary JSON value.
             *
             * You should usually call [Builder.suffix] with a well-typed [String] value instead.
             * This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun suffix(suffix: JsonField<String>) = apply { this.suffix = suffix }

            /**
             * What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make
             * the output more random, while lower values like 0.2 will make it more focused and
             * deterministic.
             *
             * We generally recommend altering this or `top_p` but not both.
             */
            fun temperature(temperature: Double?) = temperature(JsonField.ofNullable(temperature))

            /**
             * Alias for [Builder.temperature].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun temperature(temperature: Double) = temperature(temperature as Double?)

            /** Alias for calling [Builder.temperature] with `temperature.orElse(null)`. */
            fun temperature(temperature: Optional<Double>) = temperature(temperature.getOrNull())

            /**
             * Sets [Builder.temperature] to an arbitrary JSON value.
             *
             * You should usually call [Builder.temperature] with a well-typed [Double] value
             * instead. This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun temperature(temperature: JsonField<Double>) = apply {
                this.temperature = temperature
            }

            /**
             * An alternative to sampling with temperature, called nucleus sampling, where the model
             * considers the results of the tokens with top_p probability mass. So 0.1 means only
             * the tokens comprising the top 10% probability mass are considered.
             *
             * We generally recommend altering this or `temperature` but not both.
             */
            fun topP(topP: Double?) = topP(JsonField.ofNullable(topP))

            /**
             * Alias for [Builder.topP].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun topP(topP: Double) = topP(topP as Double?)

            /** Alias for calling [Builder.topP] with `topP.orElse(null)`. */
            fun topP(topP: Optional<Double>) = topP(topP.getOrNull())

            /**
             * Sets [Builder.topP] to an arbitrary JSON value.
             *
             * You should usually call [Builder.topP] with a well-typed [Double] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun topP(topP: JsonField<Double>) = apply { this.topP = topP }

            /**
             * A unique identifier representing your end-user, which can help OpenAI to monitor and
             * detect abuse.
             * [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
             */
            fun user(user: String) = user(JsonField.of(user))

            /**
             * Sets [Builder.user] to an arbitrary JSON value.
             *
             * You should usually call [Builder.user] with a well-typed [String] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun user(user: JsonField<String>) = apply { this.user = user }

            fun additionalProperties(additionalProperties: Map<String, JsonValue>) = apply {
                this.additionalProperties.clear()
                putAllAdditionalProperties(additionalProperties)
            }

            fun putAdditionalProperty(key: String, value: JsonValue) = apply {
                additionalProperties.put(key, value)
            }

            fun putAllAdditionalProperties(additionalProperties: Map<String, JsonValue>) = apply {
                this.additionalProperties.putAll(additionalProperties)
            }

            fun removeAdditionalProperty(key: String) = apply { additionalProperties.remove(key) }

            fun removeAllAdditionalProperties(keys: Set<String>) = apply {
                keys.forEach(::removeAdditionalProperty)
            }

            /**
             * Returns an immutable instance of [Body].
             *
             * Further updates to this [Builder] will not mutate the returned instance.
             *
             * The following fields are required:
             * ```java
             * .model()
             * .prompt()
             * ```
             *
             * @throws IllegalStateException if any required field is unset.
             */
            fun build(): Body =
                Body(
                    checkRequired("model", model),
                    checkRequired("prompt", prompt),
                    bestOf,
                    echo,
                    frequencyPenalty,
                    logitBias,
                    logprobs,
                    maxTokens,
                    n,
                    presencePenalty,
                    seed,
                    stop,
                    streamOptions,
                    suffix,
                    temperature,
                    topP,
                    user,
                    additionalProperties.toMutableMap(),
                )
        }

        private var validated: Boolean = false

        fun validate(): Body = apply {
            if (validated) {
                return@apply
            }

            model()
            prompt().ifPresent { it.validate() }
            bestOf()
            echo()
            frequencyPenalty()
            logitBias().ifPresent { it.validate() }
            logprobs()
            maxTokens()
            n()
            presencePenalty()
            seed()
            stop().ifPresent { it.validate() }
            streamOptions().ifPresent { it.validate() }
            suffix()
            temperature()
            topP()
            user()
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        /**
         * Returns a score indicating how many valid values are contained in this object
         * recursively.
         *
         * Used for best match union deserialization.
         */
        @JvmSynthetic
        internal fun validity(): Int =
            (if (model.asKnown().isPresent) 1 else 0) +
                (prompt.asKnown().getOrNull()?.validity() ?: 0) +
                (if (bestOf.asKnown().isPresent) 1 else 0) +
                (if (echo.asKnown().isPresent) 1 else 0) +
                (if (frequencyPenalty.asKnown().isPresent) 1 else 0) +
                (logitBias.asKnown().getOrNull()?.validity() ?: 0) +
                (if (logprobs.asKnown().isPresent) 1 else 0) +
                (if (maxTokens.asKnown().isPresent) 1 else 0) +
                (if (n.asKnown().isPresent) 1 else 0) +
                (if (presencePenalty.asKnown().isPresent) 1 else 0) +
                (if (seed.asKnown().isPresent) 1 else 0) +
                (stop.asKnown().getOrNull()?.validity() ?: 0) +
                (streamOptions.asKnown().getOrNull()?.validity() ?: 0) +
                (if (suffix.asKnown().isPresent) 1 else 0) +
                (if (temperature.asKnown().isPresent) 1 else 0) +
                (if (topP.asKnown().isPresent) 1 else 0) +
                (if (user.asKnown().isPresent) 1 else 0)

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return /* spotless:off */ other is Body && model == other.model && prompt == other.prompt && bestOf == other.bestOf && echo == other.echo && frequencyPenalty == other.frequencyPenalty && logitBias == other.logitBias && logprobs == other.logprobs && maxTokens == other.maxTokens && n == other.n && presencePenalty == other.presencePenalty && seed == other.seed && stop == other.stop && streamOptions == other.streamOptions && suffix == other.suffix && temperature == other.temperature && topP == other.topP && user == other.user && additionalProperties == other.additionalProperties /* spotless:on */
        }

        /* spotless:off */
        private val hashCode: Int by lazy { Objects.hash(model, prompt, bestOf, echo, frequencyPenalty, logitBias, logprobs, maxTokens, n, presencePenalty, seed, stop, streamOptions, suffix, temperature, topP, user, additionalProperties) }
        /* spotless:on */

        override fun hashCode(): Int = hashCode

        override fun toString() =
            "Body{model=$model, prompt=$prompt, bestOf=$bestOf, echo=$echo, frequencyPenalty=$frequencyPenalty, logitBias=$logitBias, logprobs=$logprobs, maxTokens=$maxTokens, n=$n, presencePenalty=$presencePenalty, seed=$seed, stop=$stop, streamOptions=$streamOptions, suffix=$suffix, temperature=$temperature, topP=$topP, user=$user, additionalProperties=$additionalProperties}"
    }

    /**
     * ID of the model to use. You can use the
     * [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of
     * your available models, or see our [Model overview](https://platform.openai.com/docs/models)
     * for descriptions of them.
     */
    class Model @JsonCreator private constructor(private val value: JsonField<String>) : Enum {

        /**
         * Returns this class instance's raw value.
         *
         * This is usually only useful if this instance was deserialized from data that doesn't
         * match any known member, and you want to know that value. For example, if the SDK is on an
         * older version than the API, then the API may respond with new members that the SDK is
         * unaware of.
         */
        @com.fasterxml.jackson.annotation.JsonValue fun _value(): JsonField<String> = value

        companion object {

            @JvmField val GPT_3_5_TURBO_INSTRUCT = of("gpt-3.5-turbo-instruct")

            @JvmField val DAVINCI_002 = of("davinci-002")

            @JvmField val BABBAGE_002 = of("babbage-002")

            @JvmStatic fun of(value: String) = Model(JsonField.of(value))
        }

        /** An enum containing [Model]'s known values. */
        enum class Known {
            GPT_3_5_TURBO_INSTRUCT,
            DAVINCI_002,
            BABBAGE_002,
        }

        /**
         * An enum containing [Model]'s known values, as well as an [_UNKNOWN] member.
         *
         * An instance of [Model] can contain an unknown value in a couple of cases:
         * - It was deserialized from data that doesn't match any known member. For example, if the
         *   SDK is on an older version than the API, then the API may respond with new members that
         *   the SDK is unaware of.
         * - It was constructed with an arbitrary value using the [of] method.
         */
        enum class Value {
            GPT_3_5_TURBO_INSTRUCT,
            DAVINCI_002,
            BABBAGE_002,
            /** An enum member indicating that [Model] was instantiated with an unknown value. */
            _UNKNOWN,
        }

        /**
         * Returns an enum member corresponding to this class instance's value, or [Value._UNKNOWN]
         * if the class was instantiated with an unknown value.
         *
         * Use the [known] method instead if you're certain the value is always known or if you want
         * to throw for the unknown case.
         */
        fun value(): Value =
            when (this) {
                GPT_3_5_TURBO_INSTRUCT -> Value.GPT_3_5_TURBO_INSTRUCT
                DAVINCI_002 -> Value.DAVINCI_002
                BABBAGE_002 -> Value.BABBAGE_002
                else -> Value._UNKNOWN
            }

        /**
         * Returns an enum member corresponding to this class instance's value.
         *
         * Use the [value] method instead if you're uncertain the value is always known and don't
         * want to throw for the unknown case.
         *
         * @throws OpenAIInvalidDataException if this class instance's value is a not a known
         *   member.
         */
        fun known(): Known =
            when (this) {
                GPT_3_5_TURBO_INSTRUCT -> Known.GPT_3_5_TURBO_INSTRUCT
                DAVINCI_002 -> Known.DAVINCI_002
                BABBAGE_002 -> Known.BABBAGE_002
                else -> throw OpenAIInvalidDataException("Unknown Model: $value")
            }

        /**
         * Returns this class instance's primitive wire representation.
         *
         * This differs from the [toString] method because that method is primarily for debugging
         * and generally doesn't throw.
         *
         * @throws OpenAIInvalidDataException if this class instance's value does not have the
         *   expected primitive type.
         */
        fun asString(): String =
            _value().asString().orElseThrow { OpenAIInvalidDataException("Value is not a String") }

        private var validated: Boolean = false

        fun validate(): Model = apply {
            if (validated) {
                return@apply
            }

            known()
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        /**
         * Returns a score indicating how many valid values are contained in this object
         * recursively.
         *
         * Used for best match union deserialization.
         */
        @JvmSynthetic internal fun validity(): Int = if (value() == Value._UNKNOWN) 0 else 1

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return /* spotless:off */ other is Model && value == other.value /* spotless:on */
        }

        override fun hashCode() = value.hashCode()

        override fun toString() = value.toString()
    }

    /**
     * The prompt(s) to generate completions for, encoded as a string, array of strings, array of
     * tokens, or array of token arrays.
     *
     * Note that <|endoftext|> is the document separator that the model sees during training, so if
     * a prompt is not specified the model will generate as if from the beginning of a new document.
     */
    @JsonDeserialize(using = Prompt.Deserializer::class)
    @JsonSerialize(using = Prompt.Serializer::class)
    class Prompt
    private constructor(
        private val string: String? = null,
        private val arrayOfStrings: List<String>? = null,
        private val arrayOfTokens: List<Long>? = null,
        private val arrayOfTokenArrays: List<List<Long>>? = null,
        private val _json: JsonValue? = null,
    ) {

        fun string(): Optional<String> = Optional.ofNullable(string)

        fun arrayOfStrings(): Optional<List<String>> = Optional.ofNullable(arrayOfStrings)

        fun arrayOfTokens(): Optional<List<Long>> = Optional.ofNullable(arrayOfTokens)

        fun arrayOfTokenArrays(): Optional<List<List<Long>>> =
            Optional.ofNullable(arrayOfTokenArrays)

        fun isString(): Boolean = string != null

        fun isArrayOfStrings(): Boolean = arrayOfStrings != null

        fun isArrayOfTokens(): Boolean = arrayOfTokens != null

        fun isArrayOfTokenArrays(): Boolean = arrayOfTokenArrays != null

        fun asString(): String = string.getOrThrow("string")

        fun asArrayOfStrings(): List<String> = arrayOfStrings.getOrThrow("arrayOfStrings")

        fun asArrayOfTokens(): List<Long> = arrayOfTokens.getOrThrow("arrayOfTokens")

        fun asArrayOfTokenArrays(): List<List<Long>> =
            arrayOfTokenArrays.getOrThrow("arrayOfTokenArrays")

        fun _json(): Optional<JsonValue> = Optional.ofNullable(_json)

        fun <T> accept(visitor: Visitor<T>): T =
            when {
                string != null -> visitor.visitString(string)
                arrayOfStrings != null -> visitor.visitArrayOfStrings(arrayOfStrings)
                arrayOfTokens != null -> visitor.visitArrayOfTokens(arrayOfTokens)
                arrayOfTokenArrays != null -> visitor.visitArrayOfTokenArrays(arrayOfTokenArrays)
                else -> visitor.unknown(_json)
            }

        private var validated: Boolean = false

        fun validate(): Prompt = apply {
            if (validated) {
                return@apply
            }

            accept(
                object : Visitor<Unit> {
                    override fun visitString(string: String) {}

                    override fun visitArrayOfStrings(arrayOfStrings: List<String>) {}

                    override fun visitArrayOfTokens(arrayOfTokens: List<Long>) {}

                    override fun visitArrayOfTokenArrays(arrayOfTokenArrays: List<List<Long>>) {}
                }
            )
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        /**
         * Returns a score indicating how many valid values are contained in this object
         * recursively.
         *
         * Used for best match union deserialization.
         */
        @JvmSynthetic
        internal fun validity(): Int =
            accept(
                object : Visitor<Int> {
                    override fun visitString(string: String) = 1

                    override fun visitArrayOfStrings(arrayOfStrings: List<String>) =
                        arrayOfStrings.size

                    override fun visitArrayOfTokens(arrayOfTokens: List<Long>) = arrayOfTokens.size

                    override fun visitArrayOfTokenArrays(arrayOfTokenArrays: List<List<Long>>) =
                        arrayOfTokenArrays.sumOf { it.size.toInt() }

                    override fun unknown(json: JsonValue?) = 0
                }
            )

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return /* spotless:off */ other is Prompt && string == other.string && arrayOfStrings == other.arrayOfStrings && arrayOfTokens == other.arrayOfTokens && arrayOfTokenArrays == other.arrayOfTokenArrays /* spotless:on */
        }

        override fun hashCode(): Int = /* spotless:off */ Objects.hash(string, arrayOfStrings, arrayOfTokens, arrayOfTokenArrays) /* spotless:on */

        override fun toString(): String =
            when {
                string != null -> "Prompt{string=$string}"
                arrayOfStrings != null -> "Prompt{arrayOfStrings=$arrayOfStrings}"
                arrayOfTokens != null -> "Prompt{arrayOfTokens=$arrayOfTokens}"
                arrayOfTokenArrays != null -> "Prompt{arrayOfTokenArrays=$arrayOfTokenArrays}"
                _json != null -> "Prompt{_unknown=$_json}"
                else -> throw IllegalStateException("Invalid Prompt")
            }

        companion object {

            @JvmStatic fun ofString(string: String) = Prompt(string = string)

            @JvmStatic
            fun ofArrayOfStrings(arrayOfStrings: List<String>) =
                Prompt(arrayOfStrings = arrayOfStrings)

            @JvmStatic
            fun ofArrayOfTokens(arrayOfTokens: List<Long>) = Prompt(arrayOfTokens = arrayOfTokens)

            @JvmStatic
            fun ofArrayOfTokenArrays(arrayOfTokenArrays: List<List<Long>>) =
                Prompt(arrayOfTokenArrays = arrayOfTokenArrays)
        }

        /** An interface that defines how to map each variant of [Prompt] to a value of type [T]. */
        interface Visitor<out T> {

            fun visitString(string: String): T

            fun visitArrayOfStrings(arrayOfStrings: List<String>): T

            fun visitArrayOfTokens(arrayOfTokens: List<Long>): T

            fun visitArrayOfTokenArrays(arrayOfTokenArrays: List<List<Long>>): T

            /**
             * Maps an unknown variant of [Prompt] to a value of type [T].
             *
             * An instance of [Prompt] can contain an unknown variant if it was deserialized from
             * data that doesn't match any known variant. For example, if the SDK is on an older
             * version than the API, then the API may respond with new variants that the SDK is
             * unaware of.
             *
             * @throws OpenAIInvalidDataException in the default implementation.
             */
            fun unknown(json: JsonValue?): T {
                throw OpenAIInvalidDataException("Unknown Prompt: $json")
            }
        }

        internal class Deserializer : BaseDeserializer<Prompt>(Prompt::class) {

            override fun ObjectCodec.deserialize(node: JsonNode): Prompt {
                val json = JsonValue.fromJsonNode(node)

                val bestMatches =
                    sequenceOf(
                            tryDeserialize(node, jacksonTypeRef<String>())?.let {
                                Prompt(string = it, _json = json)
                            },
                            tryDeserialize(node, jacksonTypeRef<List<String>>())?.let {
                                Prompt(arrayOfStrings = it, _json = json)
                            },
                            tryDeserialize(node, jacksonTypeRef<List<Long>>())?.let {
                                Prompt(arrayOfTokens = it, _json = json)
                            },
                            tryDeserialize(node, jacksonTypeRef<List<List<Long>>>())?.let {
                                Prompt(arrayOfTokenArrays = it, _json = json)
                            },
                        )
                        .filterNotNull()
                        .allMaxBy { it.validity() }
                        .toList()
                return when (bestMatches.size) {
                    // This can happen if what we're deserializing is completely incompatible with
                    // all the possible variants (e.g. deserializing from object).
                    0 -> Prompt(_json = json)
                    1 -> bestMatches.single()
                    // If there's more than one match with the highest validity, then use the first
                    // completely valid match, or simply the first match if none are completely
                    // valid.
                    else -> bestMatches.firstOrNull { it.isValid() } ?: bestMatches.first()
                }
            }
        }

        internal class Serializer : BaseSerializer<Prompt>(Prompt::class) {

            override fun serialize(
                value: Prompt,
                generator: JsonGenerator,
                provider: SerializerProvider,
            ) {
                when {
                    value.string != null -> generator.writeObject(value.string)
                    value.arrayOfStrings != null -> generator.writeObject(value.arrayOfStrings)
                    value.arrayOfTokens != null -> generator.writeObject(value.arrayOfTokens)
                    value.arrayOfTokenArrays != null ->
                        generator.writeObject(value.arrayOfTokenArrays)
                    value._json != null -> generator.writeObject(value._json)
                    else -> throw IllegalStateException("Invalid Prompt")
                }
            }
        }
    }

    /**
     * Modify the likelihood of specified tokens appearing in the completion.
     *
     * Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to
     * an associated bias value from -100 to 100. You can use this
     * [tokenizer tool](/tokenizer?view=bpe) to convert text to token IDs. Mathematically, the bias
     * is added to the logits generated by the model prior to sampling. The exact effect will vary
     * per model, but values between -1 and 1 should decrease or increase likelihood of selection;
     * values like -100 or 100 should result in a ban or exclusive selection of the relevant token.
     *
     * As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from being
     * generated.
     */
    class LogitBias
    @JsonCreator
    private constructor(
        @com.fasterxml.jackson.annotation.JsonValue
        private val additionalProperties: Map<String, JsonValue>
    ) {

        @JsonAnyGetter
        @ExcludeMissing
        fun _additionalProperties(): Map<String, JsonValue> = additionalProperties

        fun toBuilder() = Builder().from(this)

        companion object {

            /** Returns a mutable builder for constructing an instance of [LogitBias]. */
            @JvmStatic fun builder() = Builder()
        }

        /** A builder for [LogitBias]. */
        class Builder internal constructor() {

            private var additionalProperties: MutableMap<String, JsonValue> = mutableMapOf()

            @JvmSynthetic
            internal fun from(logitBias: LogitBias) = apply {
                additionalProperties = logitBias.additionalProperties.toMutableMap()
            }

            fun additionalProperties(additionalProperties: Map<String, JsonValue>) = apply {
                this.additionalProperties.clear()
                putAllAdditionalProperties(additionalProperties)
            }

            fun putAdditionalProperty(key: String, value: JsonValue) = apply {
                additionalProperties.put(key, value)
            }

            fun putAllAdditionalProperties(additionalProperties: Map<String, JsonValue>) = apply {
                this.additionalProperties.putAll(additionalProperties)
            }

            fun removeAdditionalProperty(key: String) = apply { additionalProperties.remove(key) }

            fun removeAllAdditionalProperties(keys: Set<String>) = apply {
                keys.forEach(::removeAdditionalProperty)
            }

            /**
             * Returns an immutable instance of [LogitBias].
             *
             * Further updates to this [Builder] will not mutate the returned instance.
             */
            fun build(): LogitBias = LogitBias(additionalProperties.toImmutable())
        }

        private var validated: Boolean = false

        fun validate(): LogitBias = apply {
            if (validated) {
                return@apply
            }

            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        /**
         * Returns a score indicating how many valid values are contained in this object
         * recursively.
         *
         * Used for best match union deserialization.
         */
        @JvmSynthetic
        internal fun validity(): Int =
            additionalProperties.count { (_, value) -> !value.isNull() && !value.isMissing() }

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return /* spotless:off */ other is LogitBias && additionalProperties == other.additionalProperties /* spotless:on */
        }

        /* spotless:off */
        private val hashCode: Int by lazy { Objects.hash(additionalProperties) }
        /* spotless:on */

        override fun hashCode(): Int = hashCode

        override fun toString() = "LogitBias{additionalProperties=$additionalProperties}"
    }

    /**
     * Not supported with latest reasoning models `o3` and `o4-mini`.
     *
     * Up to 4 sequences where the API will stop generating further tokens. The returned text will
     * not contain the stop sequence.
     */
    @JsonDeserialize(using = Stop.Deserializer::class)
    @JsonSerialize(using = Stop.Serializer::class)
    class Stop
    private constructor(
        private val string: String? = null,
        private val strings: List<String>? = null,
        private val _json: JsonValue? = null,
    ) {

        fun string(): Optional<String> = Optional.ofNullable(string)

        fun strings(): Optional<List<String>> = Optional.ofNullable(strings)

        fun isString(): Boolean = string != null

        fun isStrings(): Boolean = strings != null

        fun asString(): String = string.getOrThrow("string")

        fun asStrings(): List<String> = strings.getOrThrow("strings")

        fun _json(): Optional<JsonValue> = Optional.ofNullable(_json)

        fun <T> accept(visitor: Visitor<T>): T =
            when {
                string != null -> visitor.visitString(string)
                strings != null -> visitor.visitStrings(strings)
                else -> visitor.unknown(_json)
            }

        private var validated: Boolean = false

        fun validate(): Stop = apply {
            if (validated) {
                return@apply
            }

            accept(
                object : Visitor<Unit> {
                    override fun visitString(string: String) {}

                    override fun visitStrings(strings: List<String>) {}
                }
            )
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        /**
         * Returns a score indicating how many valid values are contained in this object
         * recursively.
         *
         * Used for best match union deserialization.
         */
        @JvmSynthetic
        internal fun validity(): Int =
            accept(
                object : Visitor<Int> {
                    override fun visitString(string: String) = 1

                    override fun visitStrings(strings: List<String>) = strings.size

                    override fun unknown(json: JsonValue?) = 0
                }
            )

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return /* spotless:off */ other is Stop && string == other.string && strings == other.strings /* spotless:on */
        }

        override fun hashCode(): Int = /* spotless:off */ Objects.hash(string, strings) /* spotless:on */

        override fun toString(): String =
            when {
                string != null -> "Stop{string=$string}"
                strings != null -> "Stop{strings=$strings}"
                _json != null -> "Stop{_unknown=$_json}"
                else -> throw IllegalStateException("Invalid Stop")
            }

        companion object {

            @JvmStatic fun ofString(string: String) = Stop(string = string)

            @JvmStatic fun ofStrings(strings: List<String>) = Stop(strings = strings)
        }

        /** An interface that defines how to map each variant of [Stop] to a value of type [T]. */
        interface Visitor<out T> {

            fun visitString(string: String): T

            fun visitStrings(strings: List<String>): T

            /**
             * Maps an unknown variant of [Stop] to a value of type [T].
             *
             * An instance of [Stop] can contain an unknown variant if it was deserialized from data
             * that doesn't match any known variant. For example, if the SDK is on an older version
             * than the API, then the API may respond with new variants that the SDK is unaware of.
             *
             * @throws OpenAIInvalidDataException in the default implementation.
             */
            fun unknown(json: JsonValue?): T {
                throw OpenAIInvalidDataException("Unknown Stop: $json")
            }
        }

        internal class Deserializer : BaseDeserializer<Stop>(Stop::class) {

            override fun ObjectCodec.deserialize(node: JsonNode): Stop {
                val json = JsonValue.fromJsonNode(node)

                val bestMatches =
                    sequenceOf(
                            tryDeserialize(node, jacksonTypeRef<String>())?.let {
                                Stop(string = it, _json = json)
                            },
                            tryDeserialize(node, jacksonTypeRef<List<String>>())?.let {
                                Stop(strings = it, _json = json)
                            },
                        )
                        .filterNotNull()
                        .allMaxBy { it.validity() }
                        .toList()
                return when (bestMatches.size) {
                    // This can happen if what we're deserializing is completely incompatible with
                    // all the possible variants (e.g. deserializing from object).
                    0 -> Stop(_json = json)
                    1 -> bestMatches.single()
                    // If there's more than one match with the highest validity, then use the first
                    // completely valid match, or simply the first match if none are completely
                    // valid.
                    else -> bestMatches.firstOrNull { it.isValid() } ?: bestMatches.first()
                }
            }
        }

        internal class Serializer : BaseSerializer<Stop>(Stop::class) {

            override fun serialize(
                value: Stop,
                generator: JsonGenerator,
                provider: SerializerProvider,
            ) {
                when {
                    value.string != null -> generator.writeObject(value.string)
                    value.strings != null -> generator.writeObject(value.strings)
                    value._json != null -> generator.writeObject(value._json)
                    else -> throw IllegalStateException("Invalid Stop")
                }
            }
        }
    }

    override fun equals(other: Any?): Boolean {
        if (this === other) {
            return true
        }

        return /* spotless:off */ other is CompletionCreateParams && body == other.body && additionalHeaders == other.additionalHeaders && additionalQueryParams == other.additionalQueryParams /* spotless:on */
    }

    override fun hashCode(): Int = /* spotless:off */ Objects.hash(body, additionalHeaders, additionalQueryParams) /* spotless:on */

    override fun toString() =
        "CompletionCreateParams{body=$body, additionalHeaders=$additionalHeaders, additionalQueryParams=$additionalQueryParams}"
}
